The effects of dietary macronutrient composition on resting energy expenditure following active weight loss: A systematic review and meta-analysis.

A systematic review and meta-analysis was conducted to evaluate the relative effectiveness of different dietary macronutrient patterns on changes in resting energy expenditure (REE) in relation to weight loss, categorized as minimal (<5%) and moderate to high (>5%). Changes in REE were assessed using a DerSimonian and Laird random-effects meta-analysis. A diet lower in carbohydrates (CHO) or higher in fat and protein was associated with smaller reductions in REE, with these trends being more pronounced among participants who experienced moderate to high weight loss. Adjusted meta-regression analysis indicated that, within the participants who experienced moderate to high weight loss, each 1% increase in CHO intake was associated with a reduction of 2.30 kcal/day in REE (95% CI: -4.11 to -0.47, p = 0.013). In contrast, a 1% increase in protein and fat intake was correlated with an increase in REE by 3.00 (95% confidence interval [CI] [1.02, 5.07], p = 0.003) and 0.5 (95% CI [-2.43, 3.41], p = 0.740) kcal/day, respectively. No significant associations were found among participants who experienced minimal weight loss. These findings indicate that, under a caloric deficit, the impact of dietary macronutrient composition on REE may vary depending on the degree of weight loss and individual metabolic responses.

Pituitary Suppression with Gonadotropin-Releasing Hormone Agonist Prior to Artificial Endometrial Preparation in Frozen-Thawed Embryo Transfer Cycles: A Systematic Review and Meta-Analysis of Different Protocols and Infertile Populations.

This study investigates the effect of GnRHa pretreatment on pregnancy outcomes in artificial endometrial preparation for frozen-thawed embryo transfer (AC-FET) cycles. A systematic review of English language studies published before 1 September 2022, was conducted, excluding conference papers and preprints. Forty-one studies involving 43,021 participants were analyzed using meta-analysis, with a sensitivity analysis ensuring result robustness. The study found that GnRHa pretreatment generally improved the clinical pregnancy rate (CPR), implantation rate (IR), and live birth rate (LBR). However, discrepancies existed between randomized controlled trials (RCTs) and observational studies; RCTs showed no significant differences in outcomes for GnRHa-treated cycles. Depot GnRHa protocols outperformed daily regimens in LBR. Extended GnRHa pretreatment (two to five cycles) significantly improved CPR and IR compared to shorter treatment. Women with polycystic ovary syndrome (PCOS) saw substantial benefits from GnRHa pretreatment, including improved CPR and LBR and reduced miscarriage rates. In contrast, no significant benefits were observed in women with regular menstruation. More rigorous research is needed to solidify these findings.

Predicting EGFR Mutation Status in Non-Small Cell Lung Cancer Using Artificial Intelligence: A Systematic Review and Meta-Analysis.

RATIONALE AND OBJECTIVES: Recent advancements in artificial intelligence (AI) render a substantial promise for epidermal growth factor receptor (EGFR) mutation status prediction in non-small cell lung cancer (NSCLC). We aimed to evaluate the performance and quality of AI algorithms that use radiomics features in predicting EGFR mutation status in patient with NSCLC. MATERIALS AND METHODS: We searched PubMed (Medline), EMBASE, Web of Science, and IEEExplore for studies published up to February 28, 2022. Studies utilizing an AI algorithm (either conventional machine learning [cML] and deep learning [DL]) for predicting EGFR mutations in patients with NSLCL were included. We extracted binary diagnostic accuracy data and constructed a bivariate random-effects model to obtain pooled sensitivity, specificity, and 95% confidence interval. This study is registered with PROSPERO, CRD42021278738. RESULTS: Our search identified 460 studies, of which 42 were included. Thirty-five studies were included in the meta-analysis. The AI algorithms exhibited an overall area under the curve (AUC) value of 0.789 and pooled sensitivity and specificity levels of 72.2% and 73.3%, respectively. The DL algorithms outperformed cML in terms of AUC (0.822 vs. 0.775) and sensitivity (80.1% vs. 71.1%), but had lower specificity (70.0% vs. 73.8%, p-value < 0.001) compared to cML. Subgroup analysis revealed that the use of positron-emission tomography/computed tomography, additional clinical information, deep feature extraction, and manual segmentation can improve diagnostic performance. CONCLUSION: DL algorithms can serve as a novel method for increasing predictive accuracy and thus have considerable potential for use in predicting EGFR mutation status in patient with NSCLC. We also suggest that guidelines on using AI algorithms in medical image analysis should be developed with a focus on oncologic radiomics.

Consistency and Accuracy of Artificial Intelligence for Providing Nutritional Information.

This cross-sectional study analyzes the accuracy of nutrition information from artificial intelligence (AI) in comparison with a nutritionist.

Mitigating errors in mobile-based dietary assessments: Effects of a data modification process on the validity of an image-assisted food and nutrition app.

OBJECTIVE: Mobile nutrition applications (apps) provide a simple way for individuals to record their diet, but the validity and inherent errors need to be carefully evaluated. The aim of this study was to assess the validity and clarify the sources of measurement errors of image-assisted mobile nutrition apps. METHODS: This was a cross-sectional study with 98 students recruited from School of Nutrition and Health Sciences, Taipei Medical University. A 3-d nutrient intake record by Formosa Food and Nutrient Recording App (FoodApp) was compared with a 24-h dietary recall (24-HDR). A two-stage data modification process, manual data cleaning, and reanalyzing of prepackaged foods were employed to address inherent errors. Nutrient intake levels obtained by the two methods were compared with the recommended daily intake (DRI), Taiwan. Paired t test, Spearman's correlation coefficients, and Bland-Altman plots were used to assess agreement between the FoodApp and 24-HDR. RESULTS: Manual data cleaning identified 166 food coding errors (12%; stage 1), and 426 food codes with missing micronutrients (32%) were reanalyzed (stage 2). Positive linear trends were observed for total energy and micronutrient intake (all Ptrend < 0.05) after the two stages of data modification, but not for dietary fat, carbohydrates, or vitamin D. There were no statistical differences in mean energy and macronutrient intake between the FoodApp and 24-HDR, and this agreement was confirmed by Bland-Altman plots. Spearman's correlation analyses showed strong to moderate correlations (r = 0.834 ∼ 0.386) between the two methods. Participants' nutrient intake tended to be lower than the DRI, but no differences in proportions of adequacy/inadequacy for DRI values were observed between the two methods. CONCLUSIONS: Mitigating errors significantly improved the accuracy of the Formosa FoodApp, indicating its validity and reliability as a self-reporting mobile-based dietary assessment tool. Dietitians and health professionals should be mindful of potential errors associated with self-reporting nutrition apps, and manual data cleaning is vital to obtain reliable nutrient intake data.

Global prevalence of post-COVID-19 sleep disturbances in adults at different follow-up time points: A systematic review and meta-analysis.

Our systematic review and meta-analysis estimated the prevalence of post-COVID sleep disturbances in adult population. We systematically searched relevant studies from four databases that reported post-COVID sleep disturbances prevalence with a mean or median follow-up duration of ≥28 days. We identified 153 eligible papers, with a total COVID-19 population of 252437. Employing multilevel mixed-effects meta-analyses, we estimated the overall pooled prevalence of post-COVID sleep disturbances being 28.98% (25.73-32.34), with the highest prevalence reported in Europe and the lowest in Southeast Asia. Poor sleep quality was the most prevalent definition of sleep disturbances, followed by excessive daytime sleepiness, insomnia, sleep apnea. Prevalence estimates were notably higher when measured with Epworth sleepiness scale, or Pittsburgh sleep quality index compared to symptom questionnaires, self-reports, or personal interviews. Female sex (Odds ratio, OR = 1.59, 1.38-1.83) and severe/critical acute COVID-19 (OR = 1.36, 1.09-1.69) emerged as substantial risk factors. Our review underscore the persistent prevalence of sleep disturbances among COVID-19 survivors, and the importance of factors such as geography, definition, measures of sleep disorders, sex, and severity of acute COVID-19 infection. These findings highlight the urgent need for further investigation into the underlying molecular mechanisms driving these sleep disturbances to develop effective therapeutic strategies.

Association of diabetes mellitus with early-onset colorectal cancer: A systematic review and meta-analysis of 19 studies including 10 million individuals and 30,000 events.

BACKGROUND AND AIMS: Early-onset colorectal cancer (EoCRC) constitutes 2%-10% of all colorectal cancers and is becoming more common globally. Diabetes mellitus (DM) has increased substantially in younger adults; however, its involvement in EoCRC remains unclear. We conducted a systematic review and meta-analysis of observational studies to (1) explore the prevalence of DM in individuals with EoCRC and (2) investigate the association between DM and EoCRC. METHODS: A systematic literature search was conducted to identify studies published before May 2022 that evaluated the association between DM and EoCRC risk in four databases, including Medline (PubMed), Embase, Web of Science, and the Cochrane Central Register of Controlled Trials. Results from the studies were summarized in meta-analyses using random effects models. RESULTS: Nineteen eligible studies were included. A total of 33,359 EoCRC cases and 14,259,289 controls in 12 studies were included in the meta-analysis. The pooled odds ratio [OR] of 1.43 (95% confidence interval [CI]: 1.08-1.8) indicated significant positive association between DM and increased risk of EoCRC. Subgroup analysis demonstrated that diabetes severity was significantly associated with unmanaged DM (OR = 1.28, 95% CI: 1.02-1.6), but not with managed DM (OR = 1.04, 95% CI: 0.84-1.28). CONCLUSION: Our results suggest that DM is a risk factor for EoCRC, and the higher prevalence of DM among younger adults may contribute to the increasing incidence of EoCRC. Interventions to reduce this bidirectional risk should be further investigated for the development of effective prevention and treatment strategies. PROSPERO registration: CRD42022306347.

COVID-19 and Virtual Nutrition: A Pilot Study of Integrating Digital Food Models for Interactive Portion Size Education.

Background and aims: Digital food viewing is a vital skill for connecting dieticians to e-health. The aim of this study was to integrate a novel pedagogical framework that combines interactive three- (3-D) and two-dimensional (2-D) food models into a formal dietetic training course. The level of agreement between the digital food models (first semester) and the effectiveness of educational integration of digital food models during the school closure due to coronavirus disease 2019 (COVID-19) (second semester) were evaluated. Method: In total, 65 second-year undergraduate dietetic students were enrolled in a nutritional practicum course at the School of Nutrition and Health Sciences, Taipei Medical University (Taipei, Taiwan). A 3-D food model was created using Agisoft Metashape. Students' digital food viewing skills and receptiveness towards integrating digital food models were evaluated. Results: In the first semester, no statistical differences were observed between 2-D and 3-D food viewing skills in food identification (2-D: 89% vs. 3-D: 85%) and quantification (within ±10% difference in total calories) (2-D: 19.4% vs. 3-D: 19.3%). A Spearman correlation analysis showed moderate to strong correlations of estimated total calories (0.69~0.93; all p values < 0.05) between the 3-D and 2-D models. Further analysis showed that students who struggled to master both 2-D and 3-D food viewing skills had lower estimation accuracies than those who did not (equal performers: 28% vs. unequal performers:16%, p = 0.041), and interactive 3-D models may help them perform better than 2-D models. In the second semester, the digital food viewing skills significantly improved (food identification: 91.5% and quantification: 42.9%) even for those students who struggled to perform digital food viewing skills equally in the first semester (equal performers: 44% vs. unequal performers: 40%). Conclusion: Although repeated training greatly enhanced students' digital food viewing skills, a tailored training program may be needed to master 2-D and 3-D digital food viewing skills. Future study is needed to evaluate the effectiveness of digital food models for future "eHealth" care.

Preadmission use of antidiabetic medications and mortality among patients with COVID-19 having type 2 diabetes: A meta-analysis.

BACKGROUND: Diabetes is an independent predictor of poor outcomes in patients with COVID-19. We compared the effects of the preadmission use of antidiabetic medications on the in-hospital mortality of patients with COVID-19 having type 2 diabetes. METHODS: A systematic search of PubMed, EMBASE, Scopus and Web of Science databases was performed to include studies (except case reports and review articles) published until November 30, 2021. We excluded papers regarding in-hospital use of antidiabetic medications. We used a random-effects meta-analysis to calculate the pooled OR (95% CI) and performed a sensitivity analysis to confirm the robustness of the meta-analyses. MAIN FINDINGS: We included 61 studies (3,061,584 individuals), which were rated as having low risk of bias. The OR (95% CI) indicated some medications protective against COVID-related death, including metformin [0.54 (0.47-0.62), I2 86%], glucagon-like peptide-1 receptor agonist (GLP-1RA) [0.51 (0.37-0.69), I2 85%], and sodium-glucose transporter-2 inhibitor (SGLT-2i) [0.60 (0.40-0.88), I2 91%]. Dipeptidyl peptidase-4 inhibitor (DPP-4i) [1.23 (1.07-1.42), I2 82%] and insulin [1.70 (1.33-2.19), I2 97%] users were more likely to die during hospitalization. Sulfonylurea, thiazolidinedione, and alpha-glucosidase inhibitor were mortality neutral [0.92 (95% CI 0.83-1.01, I2 44%), 0.90 (95% CI 0.71-1.14, I2 46%), and 0.61 (95% CI 0.26-1.45, I2 77%), respectively]. The sensitivity analysis indicated that our findings were robust. CONCLUSIONS: Metformin, GLP-1RA, and SGLT-2i were associated with lower mortality rate in patients with COVID-19 having type 2 diabetes. DPP-4i and insulin were linked to increased mortality. Sulfonylurea, thiazolidinedione, and alpha-glucosidase inhibitors were mortality neutral. These findings can have a large impact on the clinicians' decisions amid the COVID-19 pandemic.

Adherence to COVID-19 nutritional guidelines and their impact on the clinical outcomes of hospitalized COVID-19 patients.

BACKGROUND & AIMS: Coronavirus disease 2019 (COVID-19) patients are at high risk of malnutrition, and their doctors are part of a multidisciplinary team, including nutritionists. However, adherence to nutritional guidelines may be difficult in the context of capacity constraints during the COVID-19 pandemic. The aim of this study was to investigate barriers to doctors' adherence to nutritional guidelines and the impacts of guideline adherence on the outcomes of hospitalized COVID-19 patients. METHODS: A multinational electronic survey involving 51 doctors was conducted between November 2020 and January 2021 from 17 COVID-19-designated hospitals in countries with high (Indonesia) and low (Vietnam) numbers of confirmed COVID-19 cases. RESULTS: In general, doctors reported concerns related to nutritional practices in patients with Covid-19 which included feeling stress when performing medical nutritional therapy (65%), lacking self-efficacy or confidence in performing nutritional care (49%), lacking clear nutritional guidelines (45%), and experiencing budget limitations (33%). A regression analysis adjusted for age, country, and the number of hospitalized COVID-19 cases revealed that guideline knowledge (ß: -1.01 (-1.78, -0.23); p = 0.012) and awareness of guidelines (ß: -1.37 (-2.66, -0.09); p = 0.037) were negatively correlated with the length of stay of critically ill COVID-19 patients, but non-significant after adjusting for specialization of the doctor. When stratified according to country, a significant relationship between guideline adherence and length of stay of critically ill patients was only found in Vietnam [guideline adherence: ß: -0.55 (-1.08, -0.03); p = 0.038; guideline knowledge: ß: -1.01 (-1.9, -0.13); p = 0.027] after adjusting for age, specialty, and number of hospitalized COVID-19 cases. In Indonesia, the significant relationship between guideline adherence and mortality of COVID-19 patients remained strong (ß: -14 (-27, -1); p = 0.033) after adjusting for age, specialty, and number of hospitalized COVID-19 cases CONCLUSIONS: Inadequate nutritional knowledge is a key barrier to guideline adherence, and this was international and may be related to doctors' specialties and the COVID-19 pandemic. Adherence to nutritional guidelines may represent a prognostic factor for survival in COVID-19 patients.

Adherence to COVID-19 Nutrition Guidelines Is Associated with Better Nutritional Management Behaviors of Hospitalized COVID-19 Patients.

Good nutritional support is crucial for the immune system to fight against coronavirus disease 2019 (COVID-19). However, in the context of a pandemic with a highly transmissible coronavirus, implementation of nutrition practice may be difficult. A multicenter electronic survey involving 62 dieticians was conducted, in order to understand barriers associated with dieticians' adherence to nutrition guidelines for hospitalized COVID-19 patients in Indonesia. 69% of dieticians felt under stress when performing nutrition care, and 90% took supplements to boost their own immunity against the coronavirus. The concerns related to clinical practice included a lack of clear guidelines (74%), a lack of access to medical records (55%), inadequate experience or knowledge (48%), and a lack of self-efficacy/confidence (29%) in performing nutritional care. Half (52%) of the dieticians had performed nutrition education/counseling, 47% had monitored a patient's body weight, and 76% had monitored a patient's dietary intake. An adjusted linear regression showed that guideline adherence independently predicted the dieticians' nutrition care behaviors of nutrition counselling (ß: 0.24 (0.002, 0.08); p = 0.04), and monitoring of body weight (ß: 0.43 (0.04, 0.11); p = 0.001) and dietary intake (ß: 0.47(0.03, 0.10); p = 0.001) of COVID-19 patients. Overall, adherence to COVID-19 nutrition guidelines is associated with better nutritional management behaviors in hospitalized COVID-19 patients.

Integration of an Image-Based Dietary Assessment Paradigm into Dietetic Training Improves Food Portion Estimates by Future Dietitians.

The use of image-based dietary assessments (IBDAs) has rapidly increased; however, there is no formalized training program to enhance the digital viewing skills of dieticians. An IBDA was integrated into a nutritional practicum course in the School of Nutrition and Health Sciences, Taipei Medical University Taiwan. An online IBDA platform was created as an off-campus remedial teaching tool to reinforce the conceptualization of food portion sizes. Dietetic students' receptiveness and response to the IBDA, and their performance in food identification and quantification, were compared between the IBDA and real food visual estimations (RFVEs). No differences were found between the IBDA and RFVE in terms of food identification (67% vs. 71%) or quantification (±10% of estimated calories: 23% vs. 24%). A Spearman correlation analysis showed a moderate to high correlation for calorie estimates between the IBDA and RFVE (r ≥ 0.33~0.75, all p < 0.0001). Repeated IBDA training significantly improved students' image-viewing skills [food identification: first semester: 67%; pretest: 77%; second semester: 84%) and quantification [±10%: first semester: 23%; pretest: 28%; second semester: 32%; and ±20%: first semester: 38%; pretest: 48%; second semester: 59%] and reduced absolute estimated errors from 27% (first semester) to 16% (second semester). Training also greatly improved the identification of omitted foods (e.g., condiments, sugar, cooking oil, and batter coatings) and the accuracy of food portion size estimates. The integration of an IBDA into dietetic courses has the potential to help students develop knowledge and skills related to "e-dietetics".

Impacts of the COVID-19 Pandemic on Food Security and Diet-Related Lifestyle Behaviors: An Analytical Study of Google Trends-Based Query Volumes.

The severe acute respiratory syndrome coronavirus (SARS-CoV)-2 disease (COVID)-19 is having profound effects on the global economy and food trade. Limited data are available on how this pandemic is affecting our dietary and lifestyle-related behaviors at the global level. Google Trends was used to obtain worldwide relative search volumes (RSVs) covering a timeframe from before the COVID-19 pandemic 1 June 2019 to 27 April 2020. Spearman's rank-order correlation coefficients were used to measure relationships between daily confirmed cases and aforementioned RSVs between 31 December 2019 and 15 April 2020. RSV curves showed increased interest in multiple keywords related to dietary and lifestyle behaviors during the COVID-19 lockdown period in March and April 2020. Spearman's correlation analysis showed that the strongest variables in each keyword category were (1) food security (food shortage: r = 0.749, food bank: r = 0.660, and free food: r = 0.555; all p < 0.001), (2) dietary behaviors (delivery: r = 0.780, restaurant: r = -0.731, take-away: r = 0.731, and food-delivery: r = 0.693; all p < 0.001), (3) outdoor-related behaviors (resort: r = -0.922, hotel: r = -0.913, cinema: r = -0.844, park: r = -0.827, fitness: r = -0.817, gym: r = -0.811; plant: r = 0.749, sunbathing: r = 0.668, and online: r = 0.670; all p < 0.001), and (4) immune-related nutrients/herbs/foods (vitamin C: r = 0.802, vitamin A: r = 0.780, zinc: r = 0.781, immune: r = 0.739, vitamin E: r = 0.707, garlic: r = 0.667, omega-3 fatty acid: r = -0.633, vitamin D: r = 0.549, and turmeric: r = 0.545; all p < 0.001). Restricted movement has affected peoples' dietary and lifestyle behaviors as people tend to search for immune-boosting nutrients/herbs and have replaced outdoor activities with sedentary indoor behaviors.

Validity of image-based dietary assessment methods: A systematic review and meta-analysis.

BACKGROUND & AIMS: Image-assisted or image-based dietary assessments (IBDAs) refer to the use of food images as the primary dietary record and have emerged as key methods for evaluating habitual dietary intake; however, the validity of image-assisted or IBDAs is still unclear, and no meta-analysis has been conducted. Our aim was to investigate the validity of IBDAs in assessing energy intake (EI) and macronutrients compared to biomarker-based (double-labeled water (DLW)) and traditional methods of 24-h dietary recall (24-HDR) and estimated/weighed food records (WFRs). METHODS: A systematic review and meta-analysis were performed according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines using the PubMed, EMBASE, and Cochrane Central Register of Controlled Trials databases. Of the 4346 papers identified, 13 studies met the inclusion criteria, comprising 606 participants. RESULTS: The overall weighted mean difference (WMD) in EI showed significant under-reporting (WMD = -179.32 kcal, 95% confidence interval (CI): -269.50 to -89.15 kcal; I2 = 89%), with the greatest difference observed between tests and DLW (WMD = -448.04 kcal, 95% CI: -755.52 to -140.56 kcal; I2 = 95%). A small non-significant trend towards under-reporting of carbohydrates (CHOs) was observed (WMD = -9.17 g, 95% CI: -20.58 to 2.24 g; I2 = 64%), but no differences were found in protein (WMD = -0.08 g, 95% CI: -3.94 to 3.79 g; I2 = 68%, p < 0.01) or fat (WMD = -0.57 g, 95% CI: -2.58 to 1.43 g; I2 = 12%, p = 0.35). A meta-regression analysis found potential effects of the body-mass index (tests vs. DLW: ß = 34.9, p = 0.063) and duration of the assessment (tests vs. WFR: ß = -66.5, p = 0.002) on EI; age (tests vs. 24-HDR: ß = -2.222, p = 0.019) and duration of the assessment (tests vs. WFR: ß = -9.19, p = 0.013) on CHO intake; duration of the assessment on protein intake (tests vs. WFR: ß = -3.2250, p = 0.0175); and duration of the assessment on fat intake (tests vs. WFR: ß = -1.07, p = 0.040). CONCLUSIONS: Except for DLW, no statistical difference was found between IBDAs and traditional methods. This suggests that like traditional methods, image-based methods have serious measurement errors, and more studies are needed to determine inherent measurement errors in IBDAs.

Use of mobile applications to improve nutrition behaviour: A systematic review.

BACKGROUND AND OBJECTIVE: Mobile applications could be effectively used for dietary intake assessment, physical activity monitoring, behavior improvement, and nutrition education. The aim of this review is to determine the effectiveness of mobile applications in improving nutrition behaviors through a systematic review of literature. METHODS: The review protocol was registered with PROSPERO: registration number CRD42018118809, and followed PRISMA guidelines. We involved original articles including mobile electronic devices for improving dietary intake, physical activity, and weight management in adult populations in this review. Data were retrieved from January 2010 to December 2018 with PubMed, Web of Science, Excerpta Medica Database (Embase), and Cumulative Index to Nursing and Allied Health Literature (CINAHL) as data sources. Authors individually screened the titles and abstracts, then full articles in order to obtain papers that met inclusion criteria. RESULTS: The database search yielded 2962 records. After removing the duplicates and analyzing the full text papers a total of 8 original articles were reviewed. Two articles showed obvious bias and were not included in our results or discussion. The remaining six articles with low to moderate bias risk were included in this systematic review. Three selected studies were randomized control trials (RCTs) with over 180 participants each. The other three studies were a nested trial, a case-control trial, and a pilot RCT with 36, 162, and 24 participants respectively. All larger RCTs and the small case control trail showed significant improvements in some nutritional-health objectives measured. The other two trials showed insignificant improvements in outcomes measured between groups. CONCLUSION: This study highlights the potential significant health benefits acquirable through mobile health application-assisted nutrition interventions. Some of these studies required significant financial and time input from providers for the application's utilization. Further studies, perhaps with multiple intervention arms, are required to compare across programs the elements that are essential for health benefits observed.